Overview

Dataset statistics

Number of variables28
Number of observations43
Missing cells189
Missing cells (%)15.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.2 KiB
Average record size in memory242.1 B

Variable types

Categorical7
Text9
Numeric12

Alerts

집계년도 has constant value ""Constant
트랙주로연장(m) is highly imbalanced (70.7%)Imbalance
트랙주로수 is highly imbalanced (57.7%)Imbalance
운영조직명 has 16 (37.2%) missing valuesMissing
부지면적(㎡) has 2 (4.7%) missing valuesMissing
건축면적(㎡) has 11 (25.6%) missing valuesMissing
연면적(㎡) has 10 (23.3%) missing valuesMissing
필드폭(m) has 1 (2.3%) missing valuesMissing
필드길이(m) has 1 (2.3%) missing valuesMissing
관람석좌석수 has 7 (16.3%) missing valuesMissing
수용인원수(명) has 6 (14.0%) missing valuesMissing
연락처 has 27 (62.8%) missing valuesMissing
홈페이지주소 has 26 (60.5%) missing valuesMissing
건설사업비(백만원) has 8 (18.6%) missing valuesMissing
비고사항 has 22 (51.2%) missing valuesMissing
소재지우편번호 has 10 (23.3%) missing valuesMissing
소재지지번주소 has 9 (20.9%) missing valuesMissing
소재지도로명주소 has 15 (34.9%) missing valuesMissing
WGS84위도 has 9 (20.9%) missing valuesMissing
WGS84경도 has 9 (20.9%) missing valuesMissing
시설명 has unique valuesUnique

Reproduction

Analysis started2023-12-22 21:34:12.771214
Analysis finished2023-12-22 21:34:15.776455
Duration3.01 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

집계년도
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size476.0 B
2021
43 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021
2nd row2021
3rd row2021
4th row2021
5th row2021

Common Values

ValueCountFrequency (%)
2021 43
100.0%

Length

2023-12-22T21:34:16.248031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-22T21:34:16.791450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 43
100.0%

시군명
Text

Distinct28
Distinct (%)65.1%
Missing0
Missing (%)0.0%
Memory size476.0 B
2023-12-22T21:34:17.391032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.0697674
Min length3

Characters and Unicode

Total characters132
Distinct characters35
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)41.9%

Sample

1st row가평군
2nd row고양시
3rd row고양시
4th row고양시
5th row과천시
ValueCountFrequency (%)
화성시 4
 
9.3%
고양시 3
 
7.0%
파주시 3
 
7.0%
용인시 3
 
7.0%
이천시 2
 
4.7%
군포시 2
 
4.7%
평택시 2
 
4.7%
연천군 2
 
4.7%
시흥시 2
 
4.7%
성남시 2
 
4.7%
Other values (18) 18
41.9%
2023-12-22T21:34:19.140011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 41
31.1%
천 8
 
6.1%
성 7
 
5.3%
주 6
 
4.5%
군 6
 
4.5%
양 6
 
4.5%
평 4
 
3.0%
포 4
 
3.0%
화 4
 
3.0%
남 4
 
3.0%
Other values (25) 42
31.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 132
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 41
31.1%
천 8
 
6.1%
성 7
 
5.3%
주 6
 
4.5%
군 6
 
4.5%
양 6
 
4.5%
평 4
 
3.0%
포 4
 
3.0%
화 4
 
3.0%
남 4
 
3.0%
Other values (25) 42
31.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 132
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 41
31.1%
천 8
 
6.1%
성 7
 
5.3%
주 6
 
4.5%
군 6
 
4.5%
양 6
 
4.5%
평 4
 
3.0%
포 4
 
3.0%
화 4
 
3.0%
남 4
 
3.0%
Other values (25) 42
31.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 132
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 41
31.1%
천 8
 
6.1%
성 7
 
5.3%
주 6
 
4.5%
군 6
 
4.5%
양 6
 
4.5%
평 4
 
3.0%
포 4
 
3.0%
화 4
 
3.0%
남 4
 
3.0%
Other values (25) 42
31.8%

시설명
Text

UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size476.0 B
2023-12-22T21:34:20.153543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length10.186047
Min length6

Characters and Unicode

Total characters438
Distinct characters96
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)100.0%

Sample

1st row가평종합운동장
2nd row고양종합운동장 보조경기장
3rd row덕양 별무리경기장
4th row고양종합운동장
5th row관문체육공원 운동장
ValueCountFrequency (%)
종합운동장 6
 
8.1%
주경기장 5
 
6.8%
보조경기장 4
 
5.4%
운동장 3
 
4.1%
공설운동장 3
 
4.1%
인조잔디구장 2
 
2.7%
파주스타디움 2
 
2.7%
고양종합운동장 2
 
2.7%
화성종합경기타운 2
 
2.7%
연천공설운동장 2
 
2.7%
Other values (43) 43
58.1%
2023-12-22T21:34:22.122460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 46
 
10.5%
운 36
 
8.2%
35
 
8.0%
동 34
 
7.8%
합 24
 
5.5%
종 23
 
5.3%
기 14
 
3.2%
경 13
 
3.0%
주 10
 
2.3%
공 9
 
2.1%
Other values (86) 194
44.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 396
90.4%
Space Separator 35
 
8.0%
Close Punctuation 3
 
0.7%
Open Punctuation 3
 
0.7%
Math Symbol 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 46
 
11.6%
운 36
 
9.1%
동 34
 
8.6%
합 24
 
6.1%
종 23
 
5.8%
기 14
 
3.5%
경 13
 
3.3%
주 10
 
2.5%
공 9
 
2.3%
시 8
 
2.0%
Other values (82) 179
45.2%
Space Separator
ValueCountFrequency (%)
35
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 396
90.4%
Common 42
 
9.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 46
 
11.6%
운 36
 
9.1%
동 34
 
8.6%
합 24
 
6.1%
종 23
 
5.8%
기 14
 
3.5%
경 13
 
3.3%
주 10
 
2.5%
공 9
 
2.3%
시 8
 
2.0%
Other values (82) 179
45.2%
Common
ValueCountFrequency (%)
35
83.3%
) 3
 
7.1%
( 3
 
7.1%
~ 1
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 396
90.4%
ASCII 42
 
9.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 46
 
11.6%
운 36
 
9.1%
동 34
 
8.6%
합 24
 
6.1%
종 23
 
5.8%
기 14
 
3.5%
경 13
 
3.3%
주 10
 
2.5%
공 9
 
2.3%
시 8
 
2.0%
Other values (82) 179
45.2%
ASCII
ValueCountFrequency (%)
35
83.3%
) 3
 
7.1%
( 3
 
7.1%
~ 1
 
2.4%

소유기관명
Text

Distinct29
Distinct (%)67.4%
Missing0
Missing (%)0.0%
Memory size476.0 B
2023-12-22T21:34:22.976948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length3
Mean length3.2093023
Min length3

Characters and Unicode

Total characters138
Distinct characters43
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)46.5%

Sample

1st row가평군
2nd row고양시
3rd row고양시
4th row고양시
5th row과천시
ValueCountFrequency (%)
화성시 4
 
9.1%
고양시 3
 
6.8%
파주시 3
 
6.8%
용인시 3
 
6.8%
평택시 2
 
4.5%
군포시 2
 
4.5%
성남시 2
 
4.5%
시흥시 2
 
4.5%
연천군 2
 
4.5%
체육회 1
 
2.3%
Other values (20) 20
45.5%
2023-12-22T21:34:24.437815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 40
29.0%
천 7
 
5.1%
성 7
 
5.1%
양 6
 
4.3%
군 6
 
4.3%
주 6
 
4.3%
인 4
 
2.9%
평 4
 
2.9%
포 4
 
2.9%
남 4
 
2.9%
Other values (33) 50
36.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 137
99.3%
Space Separator 1
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 40
29.2%
천 7
 
5.1%
성 7
 
5.1%
양 6
 
4.4%
군 6
 
4.4%
주 6
 
4.4%
인 4
 
2.9%
평 4
 
2.9%
포 4
 
2.9%
남 4
 
2.9%
Other values (32) 49
35.8%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 137
99.3%
Common 1
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 40
29.2%
천 7
 
5.1%
성 7
 
5.1%
양 6
 
4.4%
군 6
 
4.4%
주 6
 
4.4%
인 4
 
2.9%
평 4
 
2.9%
포 4
 
2.9%
남 4
 
2.9%
Other values (32) 49
35.8%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 137
99.3%
ASCII 1
 
0.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 40
29.2%
천 7
 
5.1%
성 7
 
5.1%
양 6
 
4.4%
군 6
 
4.4%
주 6
 
4.4%
인 4
 
2.9%
평 4
 
2.9%
포 4
 
2.9%
남 4
 
2.9%
Other values (32) 49
35.8%
ASCII
ValueCountFrequency (%)
1
100.0%

운영조직명
Text

MISSING 

Distinct21
Distinct (%)77.8%
Missing16
Missing (%)37.2%
Memory size476.0 B
2023-12-22T21:34:25.234565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length8.5925926
Min length2

Characters and Unicode

Total characters232
Distinct characters52
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)63.0%

Sample

1st row문화체육시설담당
2nd row고양시시설관리공단
3rd row과천시시설관리공단
4th row광주시
5th row군포시 청소년과 체육시설팀
ValueCountFrequency (%)
시설관리공단 5
 
14.3%
운영사업소 2
 
5.7%
체육시설관리사무소 2
 
5.7%
군포시 2
 
5.7%
청소년과 2
 
5.7%
체육시설팀 2
 
5.7%
평택시체육시설 2
 
5.7%
안성시 1
 
2.9%
문화체육시설담당 1
 
2.9%
수원시종합운동장관리사무소 1
 
2.9%
Other values (15) 15
42.9%
2023-12-22T21:34:27.491999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 35
15.1%
설 19
 
8.2%
관 15
 
6.5%
리 15
 
6.5%
공 14
 
6.0%
단 11
 
4.7%
10
 
4.3%
소 9
 
3.9%
사 9
 
3.9%
육 8
 
3.4%
Other values (42) 87
37.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 222
95.7%
Space Separator 10
 
4.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 35
15.8%
설 19
 
8.6%
관 15
 
6.8%
리 15
 
6.8%
공 14
 
6.3%
단 11
 
5.0%
소 9
 
4.1%
사 9
 
4.1%
육 8
 
3.6%
체 8
 
3.6%
Other values (41) 79
35.6%
Space Separator
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 222
95.7%
Common 10
 
4.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 35
15.8%
설 19
 
8.6%
관 15
 
6.8%
리 15
 
6.8%
공 14
 
6.3%
단 11
 
5.0%
소 9
 
4.1%
사 9
 
4.1%
육 8
 
3.6%
체 8
 
3.6%
Other values (41) 79
35.6%
Common
ValueCountFrequency (%)
10
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 222
95.7%
ASCII 10
 
4.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 35
15.8%
설 19
 
8.6%
관 15
 
6.8%
리 15
 
6.8%
공 14
 
6.3%
단 11
 
5.0%
소 9
 
4.1%
사 9
 
4.1%
육 8
 
3.6%
체 8
 
3.6%
Other values (41) 79
35.6%
ASCII
ValueCountFrequency (%)
10
100.0%

관리주체명
Categorical

Distinct20
Distinct (%)46.5%
Missing0
Missing (%)0.0%
Memory size476.0 B
시설관리공단
12 
화성도시공사
4 
파주시
3 
고양도시관리공사
3 
용인도시공사
3 
Other values (15)
18 

Length

Max length11
Median length6
Mean length5.8837209
Min length3

Unique

Unique12 ?
Unique (%)27.9%

Sample

1st row시설관리공단
2nd row고양도시관리공사
3rd row고양도시관리공사
4th row고양도시관리공사
5th row시설관리공단

Common Values

ValueCountFrequency (%)
시설관리공단 12
27.9%
화성도시공사 4
 
9.3%
파주시 3
 
7.0%
고양도시관리공사 3
 
7.0%
용인도시공사 3
 
7.0%
시흥시 2
 
4.7%
평택시 2
 
4.7%
성남도시개발공사 2
 
4.7%
위탁 (수원도시공사) 1
 
2.3%
위탁 (김포도시공사) 1
 
2.3%
Other values (10) 10
23.3%

Length

2023-12-22T21:34:28.632349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
시설관리공단 12
25.5%
화성도시공사 4
 
8.5%
파주시 3
 
6.4%
고양도시관리공사 3
 
6.4%
용인도시공사 3
 
6.4%
위탁 3
 
6.4%
시흥시 2
 
4.3%
평택시 2
 
4.3%
성남도시개발공사 2
 
4.3%
이천시 1
 
2.1%
Other values (12) 12
25.5%

준공연도
Real number (ℝ)

Distinct21
Distinct (%)48.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2002.1628
Minimum1984
Maximum2018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-22T21:34:29.335291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1984
5-th percentile1986
Q11996.5
median2003
Q32008.5
95-th percentile2014
Maximum2018
Range34
Interquartile range (IQR)12

Descriptive statistics

Standard deviation8.9573865
Coefficient of variation (CV)0.0044738552
Kurtosis-0.50468094
Mean2002.1628
Median Absolute Deviation (MAD)6
Skewness-0.41426134
Sum86093
Variance80.234773
MonotonicityNot monotonic
2023-12-22T21:34:30.036666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
2001 5
 
11.6%
2003 4
 
9.3%
2004 3
 
7.0%
2006 3
 
7.0%
1986 3
 
7.0%
1993 2
 
4.7%
2011 2
 
4.7%
2009 2
 
4.7%
2002 2
 
4.7%
2012 2
 
4.7%
Other values (11) 15
34.9%
ValueCountFrequency (%)
1984 1
 
2.3%
1986 3
7.0%
1987 1
 
2.3%
1990 2
 
4.7%
1993 2
 
4.7%
1994 1
 
2.3%
1996 1
 
2.3%
1997 1
 
2.3%
2001 5
11.6%
2002 2
 
4.7%
ValueCountFrequency (%)
2018 2
4.7%
2014 2
4.7%
2012 2
4.7%
2011 2
4.7%
2010 1
 
2.3%
2009 2
4.7%
2008 1
 
2.3%
2007 2
4.7%
2006 3
7.0%
2004 3
7.0%

부지면적(㎡)
Real number (ℝ)

MISSING 

Distinct40
Distinct (%)97.6%
Missing2
Missing (%)4.7%
Infinite0
Infinite (%)0.0%
Mean106955.66
Minimum8400
Maximum583905
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-22T21:34:30.921180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8400
5-th percentile12248
Q132573
median80773
Q3142200.9
95-th percentile305350
Maximum583905
Range575505
Interquartile range (IQR)109627.9

Descriptive statistics

Standard deviation110290.43
Coefficient of variation (CV)1.031179
Kurtosis7.9211271
Mean106955.66
Median Absolute Deviation (MAD)49106
Skewness2.3946287
Sum4385182.1
Variance1.2163979 × 1010
MonotonicityNot monotonic
2023-12-22T21:34:31.647582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
305350.0 2
 
4.7%
8400.0 1
 
2.3%
87447.0 1
 
2.3%
108656.0 1
 
2.3%
37900.0 1
 
2.3%
44268.16 1
 
2.3%
120016.0 1
 
2.3%
206123.0 1
 
2.3%
116475.0 1
 
2.3%
13000.0 1
 
2.3%
Other values (30) 30
69.8%
(Missing) 2
 
4.7%
ValueCountFrequency (%)
8400.0 1
2.3%
11581.0 1
2.3%
12248.0 1
2.3%
13000.0 1
2.3%
14350.0 1
2.3%
15600.0 1
2.3%
18037.0 1
2.3%
22911.0 1
2.3%
28587.0 1
2.3%
31667.0 1
2.3%
ValueCountFrequency (%)
583905.0 1
2.3%
305350.0 2
4.7%
285097.0 1
2.3%
206123.0 1
2.3%
179635.0 1
2.3%
168437.0 1
2.3%
164242.0 1
2.3%
164077.0 1
2.3%
158101.0 1
2.3%
142200.9 1
2.3%

건축면적(㎡)
Real number (ℝ)

MISSING 

Distinct32
Distinct (%)100.0%
Missing11
Missing (%)25.6%
Infinite0
Infinite (%)0.0%
Mean11412.955
Minimum528
Maximum54020.59
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-22T21:34:32.221920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum528
5-th percentile569.4455
Q12298.5
median5628
Q317131.25
95-th percentile40779.291
Maximum54020.59
Range53492.59
Interquartile range (IQR)14832.75

Descriptive statistics

Standard deviation14109.719
Coefficient of variation (CV)1.2362897
Kurtosis2.9756443
Mean11412.955
Median Absolute Deviation (MAD)4221.04
Skewness1.8356606
Sum365214.56
Variance1.9908416 × 108
MonotonicityNot monotonic
2023-12-22T21:34:32.835242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
2325.0 1
 
2.3%
1499.92 1
 
2.3%
54020.59 1
 
2.3%
2219.0 1
 
2.3%
4832.0 1
 
2.3%
2614.0 1
 
2.3%
3465.0 1
 
2.3%
16701.0 1
 
2.3%
8994.0 1
 
2.3%
32214.0 1
 
2.3%
Other values (22) 22
51.2%
(Missing) 11
25.6%
ValueCountFrequency (%)
528.0 1
2.3%
558.22 1
2.3%
578.63 1
2.3%
675.25 1
2.3%
1077.0 1
2.3%
1314.0 1
2.3%
1499.92 1
2.3%
2219.0 1
2.3%
2325.0 1
2.3%
2614.0 1
2.3%
ValueCountFrequency (%)
54020.59 1
2.3%
51247.98 1
2.3%
32214.0 1
2.3%
31943.0 1
2.3%
25569.0 1
2.3%
22223.0 1
2.3%
19040.0 1
2.3%
18422.0 1
2.3%
16701.0 1
2.3%
12313.27 1
2.3%

연면적(㎡)
Real number (ℝ)

MISSING 

Distinct33
Distinct (%)100.0%
Missing10
Missing (%)23.3%
Infinite0
Infinite (%)0.0%
Mean18622.547
Minimum463
Maximum84512.05
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-22T21:34:33.298349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum463
5-th percentile552.048
Q11852
median5277.44
Q331125
95-th percentile68315.93
Maximum84512.05
Range84049.05
Interquartile range (IQR)29273

Descriptive statistics

Standard deviation24890.501
Coefficient of variation (CV)1.3365788
Kurtosis0.69350471
Mean18622.547
Median Absolute Deviation (MAD)3917.44
Skewness1.407492
Sum614544.04
Variance6.1953705 × 108
MonotonicityNot monotonic
2023-12-22T21:34:33.751502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
11264.0 1
 
2.3%
3116.0 1
 
2.3%
5328.0 1
 
2.3%
5277.44 1
 
2.3%
84512.05 1
 
2.3%
73175.0 1
 
2.3%
31125.0 1
 
2.3%
23423.0 1
 
2.3%
463.0 1
 
2.3%
3465.0 1
 
2.3%
Other values (23) 23
53.5%
(Missing) 10
23.3%
ValueCountFrequency (%)
463.0 1
2.3%
516.12 1
2.3%
576.0 1
2.3%
931.3 1
2.3%
1360.0 1
2.3%
1599.0 1
2.3%
1710.0 1
2.3%
1712.57 1
2.3%
1852.0 1
2.3%
2325.0 1
2.3%
ValueCountFrequency (%)
84512.05 1
2.3%
73175.0 1
2.3%
65076.55 1
2.3%
59689.0 1
2.3%
58236.01 1
2.3%
53692.0 1
2.3%
37163.0 1
2.3%
32580.0 1
2.3%
31125.0 1
2.3%
23423.0 1
2.3%

트랙바닥재료명
Categorical

Distinct10
Distinct (%)23.3%
Missing0
Missing (%)0.0%
Memory size476.0 B
우레탄
24 
몬도
6 
천연탄성고무
4 
몬도트랙
3 
복합탄성고무
 
1
Other values (5)
5 

Length

Max length6
Median length3
Mean length3.4186047
Min length2

Unique

Unique6 ?
Unique (%)14.0%

Sample

1st row우레탄
2nd row천연탄성고무
3rd row천연탄성고무
4th row천연탄성고무
5th row우레탄

Common Values

ValueCountFrequency (%)
우레탄 24
55.8%
몬도 6
 
14.0%
천연탄성고무 4
 
9.3%
몬도트랙 3
 
7.0%
복합탄성고무 1
 
2.3%
쳔연탄성고무 1
 
2.3%
탄성포장재 1
 
2.3%
탄성고무 1
 
2.3%
토사 1
 
2.3%
<NA> 1
 
2.3%

Length

2023-12-22T21:34:34.341803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-22T21:34:34.951941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
우레탄 24
55.8%
몬도 6
 
14.0%
천연탄성고무 4
 
9.3%
몬도트랙 3
 
7.0%
복합탄성고무 1
 
2.3%
쳔연탄성고무 1
 
2.3%
탄성포장재 1
 
2.3%
탄성고무 1
 
2.3%
토사 1
 
2.3%
na 1
 
2.3%

트랙주로연장(m)
Categorical

IMBALANCE 

Distinct4
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Memory size476.0 B
400
39 
140
 
2
343
 
1
300
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique2 ?
Unique (%)4.7%

Sample

1st row400
2nd row400
3rd row400
4th row400
5th row400

Common Values

ValueCountFrequency (%)
400 39
90.7%
140 2
 
4.7%
343 1
 
2.3%
300 1
 
2.3%

Length

2023-12-22T21:34:35.649233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-22T21:34:36.097998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
400 39
90.7%
140 2
 
4.7%
343 1
 
2.3%
300 1
 
2.3%

트랙주로수
Categorical

IMBALANCE 

Distinct5
Distinct (%)11.6%
Missing0
Missing (%)0.0%
Memory size476.0 B
8
35 
6
5 
5
 
1
14
 
1
4
 
1

Length

Max length2
Median length1
Mean length1.0232558
Min length1

Unique

Unique3 ?
Unique (%)7.0%

Sample

1st row8
2nd row8
3rd row8
4th row8
5th row8

Common Values

ValueCountFrequency (%)
8 35
81.4%
6 5
 
11.6%
5 1
 
2.3%
14 1
 
2.3%
4 1
 
2.3%

Length

2023-12-22T21:34:36.620739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-22T21:34:36.966747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
8 35
81.4%
6 5
 
11.6%
5 1
 
2.3%
14 1
 
2.3%
4 1
 
2.3%

필드바닥재료명
Categorical

Distinct5
Distinct (%)11.6%
Missing0
Missing (%)0.0%
Memory size476.0 B
인조잔디
21 
천연잔디
19 
인조단지
 
1
<NA>
 
1
우레탄
 
1

Length

Max length4
Median length4
Mean length3.9767442
Min length3

Unique

Unique3 ?
Unique (%)7.0%

Sample

1st row인조잔디
2nd row천연잔디
3rd row인조잔디
4th row천연잔디
5th row인조잔디

Common Values

ValueCountFrequency (%)
인조잔디 21
48.8%
천연잔디 19
44.2%
인조단지 1
 
2.3%
<NA> 1
 
2.3%
우레탄 1
 
2.3%

Length

2023-12-22T21:34:37.526609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-22T21:34:37.865568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인조잔디 21
48.8%
천연잔디 19
44.2%
인조단지 1
 
2.3%
na 1
 
2.3%
우레탄 1
 
2.3%

필드폭(m)
Real number (ℝ)

MISSING 

Distinct11
Distinct (%)26.2%
Missing1
Missing (%)2.3%
Infinite0
Infinite (%)0.0%
Mean68.642857
Minimum55
Maximum105
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-22T21:34:38.231953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum55
5-th percentile60.2
Q168
median68
Q369.5
95-th percentile72
Maximum105
Range50
Interquartile range (IQR)1.5

Descriptive statistics

Standard deviation6.6838773
Coefficient of variation (CV)0.097371782
Kurtosis22.278986
Mean68.642857
Median Absolute Deviation (MAD)0
Skewness3.7580843
Sum2883
Variance44.674216
MonotonicityNot monotonic
2023-12-22T21:34:38.665121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
68 25
58.1%
70 6
 
14.0%
64 2
 
4.7%
72 2
 
4.7%
58 1
 
2.3%
60 1
 
2.3%
105 1
 
2.3%
75 1
 
2.3%
67 1
 
2.3%
71 1
 
2.3%
ValueCountFrequency (%)
55 1
 
2.3%
58 1
 
2.3%
60 1
 
2.3%
64 2
 
4.7%
67 1
 
2.3%
68 25
58.1%
70 6
 
14.0%
71 1
 
2.3%
72 2
 
4.7%
75 1
 
2.3%
ValueCountFrequency (%)
105 1
 
2.3%
75 1
 
2.3%
72 2
 
4.7%
71 1
 
2.3%
70 6
 
14.0%
68 25
58.1%
67 1
 
2.3%
64 2
 
4.7%
60 1
 
2.3%
58 1
 
2.3%

필드길이(m)
Real number (ℝ)

MISSING 

Distinct9
Distinct (%)21.4%
Missing1
Missing (%)2.3%
Infinite0
Infinite (%)0.0%
Mean103.54762
Minimum70
Maximum111
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-22T21:34:39.094057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum70
5-th percentile90.5
Q1105
median105
Q3105
95-th percentile108.8
Maximum111
Range41
Interquartile range (IQR)0

Descriptive statistics

Standard deviation6.4513276
Coefficient of variation (CV)0.062303003
Kurtosis18.611204
Mean103.54762
Median Absolute Deviation (MAD)0
Skewness-3.9914009
Sum4349
Variance41.619628
MonotonicityNot monotonic
2023-12-22T21:34:39.801991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
105 32
74.4%
104 2
 
4.7%
90 2
 
4.7%
101 1
 
2.3%
110 1
 
2.3%
111 1
 
2.3%
109 1
 
2.3%
100 1
 
2.3%
70 1
 
2.3%
(Missing) 1
 
2.3%
ValueCountFrequency (%)
70 1
 
2.3%
90 2
 
4.7%
100 1
 
2.3%
101 1
 
2.3%
104 2
 
4.7%
105 32
74.4%
109 1
 
2.3%
110 1
 
2.3%
111 1
 
2.3%
ValueCountFrequency (%)
111 1
 
2.3%
110 1
 
2.3%
109 1
 
2.3%
105 32
74.4%
104 2
 
4.7%
101 1
 
2.3%
100 1
 
2.3%
90 2
 
4.7%
70 1
 
2.3%

관람석좌석수
Real number (ℝ)

MISSING 

Distinct33
Distinct (%)91.7%
Missing7
Missing (%)16.3%
Infinite0
Infinite (%)0.0%
Mean12950.889
Minimum562
Maximum43000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-22T21:34:40.309175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum562
5-th percentile924
Q13099
median10000
Q317714.25
95-th percentile35741.25
Maximum43000
Range42438
Interquartile range (IQR)14615.25

Descriptive statistics

Standard deviation12008.78
Coefficient of variation (CV)0.92725527
Kurtosis0.20595801
Mean12950.889
Median Absolute Deviation (MAD)7121
Skewness1.0880004
Sum466232
Variance1.442108 × 108
MonotonicityNot monotonic
2023-12-22T21:34:41.202110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
1000 3
 
7.0%
10000 2
 
4.7%
2002 1
 
2.3%
35270 1
 
2.3%
12057 1
 
2.3%
5964 1
 
2.3%
12738 1
 
2.3%
696 1
 
2.3%
6300 1
 
2.3%
19428 1
 
2.3%
Other values (23) 23
53.5%
(Missing) 7
 
16.3%
ValueCountFrequency (%)
562 1
 
2.3%
696 1
 
2.3%
1000 3
7.0%
1248 1
 
2.3%
2002 1
 
2.3%
2425 1
 
2.3%
2901 1
 
2.3%
3165 1
 
2.3%
5000 1
 
2.3%
5068 1
 
2.3%
ValueCountFrequency (%)
43000 1
2.3%
37155 1
2.3%
35270 1
2.3%
35008 1
2.3%
35000 1
2.3%
28001 1
2.3%
23000 1
2.3%
21149 1
2.3%
19428 1
2.3%
17143 1
2.3%

수용인원수(명)
Real number (ℝ)

MISSING 

Distinct25
Distinct (%)67.6%
Missing6
Missing (%)14.0%
Infinite0
Infinite (%)0.0%
Mean14999.324
Minimum562
Maximum43000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-22T21:34:41.653343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum562
5-th percentile779.2
Q15000
median12000
Q325000
95-th percentile35647
Maximum43000
Range42438
Interquartile range (IQR)20000

Descriptive statistics

Standard deviation12456.521
Coefficient of variation (CV)0.83047215
Kurtosis-0.74669893
Mean14999.324
Median Absolute Deviation (MAD)9600
Skewness0.62297814
Sum554975
Variance1.5516492 × 108
MonotonicityNot monotonic
2023-12-22T21:34:42.326497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
10000 4
 
9.3%
20000 3
 
7.0%
1000 3
 
7.0%
30000 2
 
4.7%
7000 2
 
4.7%
15000 2
 
4.7%
25000 2
 
4.7%
12000 2
 
4.7%
9000 1
 
2.3%
2002 1
 
2.3%
Other values (15) 15
34.9%
(Missing) 6
 
14.0%
ValueCountFrequency (%)
562 1
 
2.3%
696 1
 
2.3%
800 1
 
2.3%
1000 3
7.0%
1300 1
 
2.3%
2002 1
 
2.3%
2425 1
 
2.3%
5000 1
 
2.3%
6100 1
 
2.3%
7000 2
4.7%
ValueCountFrequency (%)
43000 1
 
2.3%
37155 1
 
2.3%
35270 1
 
2.3%
35008 1
 
2.3%
35000 1
 
2.3%
30000 2
4.7%
27000 1
 
2.3%
25000 2
4.7%
21600 1
 
2.3%
20000 3
7.0%

좌석형태명
Categorical

Distinct6
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Memory size476.0 B
의자식
20 
<NA>
15 
계단식
5 
계단식+토성잔디
 
1
목재계단식
 
1

Length

Max length8
Median length3
Mean length3.627907
Min length3

Unique

Unique3 ?
Unique (%)7.0%

Sample

1st row계단식+토성잔디
2nd row의자식
3rd row의자식
4th row의자식
5th row목재계단식

Common Values

ValueCountFrequency (%)
의자식 20
46.5%
<NA> 15
34.9%
계단식 5
 
11.6%
계단식+토성잔디 1
 
2.3%
목재계단식 1
 
2.3%
의자식,토성잔디 1
 
2.3%

Length

2023-12-22T21:34:43.186459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-22T21:34:43.587851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
의자식 20
46.5%
na 15
34.9%
계단식 5
 
11.6%
계단식+토성잔디 1
 
2.3%
목재계단식 1
 
2.3%
의자식,토성잔디 1
 
2.3%

연락처
Text

MISSING 

Distinct14
Distinct (%)87.5%
Missing27
Missing (%)62.8%
Memory size476.0 B
2023-12-22T21:34:44.370879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters192
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)75.0%

Sample

1st row031-580-2765
2nd row031-929-4800
3rd row031-390-0418
4th row031-590-4511
5th row031-729-5870
ValueCountFrequency (%)
031-390-0418 2
12.5%
031-659-4921 2
12.5%
031-580-2765 1
 
6.2%
031-929-4800 1
 
6.2%
031-590-4511 1
 
6.2%
031-729-5870 1
 
6.2%
031-725-7100 1
 
6.2%
031-676-2773 1
 
6.2%
031-389-5215 1
 
6.2%
031-834-9585 1
 
6.2%
Other values (4) 4
25.0%
2023-12-22T21:34:45.914089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 32
16.7%
0 30
15.6%
1 27
14.1%
3 24
12.5%
9 14
7.3%
5 13
6.8%
2 12
 
6.2%
4 11
 
5.7%
8 11
 
5.7%
7 10
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 160
83.3%
Dash Punctuation 32
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 30
18.8%
1 27
16.9%
3 24
15.0%
9 14
8.8%
5 13
8.1%
2 12
 
7.5%
4 11
 
6.9%
8 11
 
6.9%
7 10
 
6.2%
6 8
 
5.0%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 192
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 32
16.7%
0 30
15.6%
1 27
14.1%
3 24
12.5%
9 14
7.3%
5 13
6.8%
2 12
 
6.2%
4 11
 
5.7%
8 11
 
5.7%
7 10
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 192
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 32
16.7%
0 30
15.6%
1 27
14.1%
3 24
12.5%
9 14
7.3%
5 13
6.8%
2 12
 
6.2%
4 11
 
5.7%
8 11
 
5.7%
7 10
 
5.2%

홈페이지주소
Text

MISSING 

Distinct14
Distinct (%)82.4%
Missing26
Missing (%)60.5%
Memory size476.0 B
2023-12-22T21:34:47.022729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length21
Mean length21.294118
Min length10

Characters and Unicode

Total characters362
Distinct characters32
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)64.7%

Sample

1st rowwww.ga21.net
2nd rowcitizenshall.or.kr
3rd rowhttp://www.gunpo21.net/
4th rowgimposisul.or.kr/
5th rowcans21.net
ValueCountFrequency (%)
http://www.gunpo21.net 2
 
11.1%
osan.go.kr 2
 
11.1%
www.pyongta.go.kr 2
 
11.1%
www.ga21.net 1
 
5.6%
citizenshall.or.kr 1
 
5.6%
gimposisul.or.kr 1
 
5.6%
cans21.net 1
 
5.6%
http//simc.or.kr 1
 
5.6%
stadium.suwon.ne.kr 1
 
5.6%
http://asimc.or.kr 1
 
5.6%
Other values (5) 5
27.8%
2023-12-22T21:34:49.107511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 41
 
11.3%
w 28
 
7.7%
t 27
 
7.5%
/ 26
 
7.2%
o 25
 
6.9%
n 23
 
6.4%
i 22
 
6.1%
r 20
 
5.5%
s 17
 
4.7%
p 15
 
4.1%
Other values (22) 118
32.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 274
75.7%
Other Punctuation 73
 
20.2%
Decimal Number 13
 
3.6%
Space Separator 1
 
0.3%
Connector Punctuation 1
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 28
 
10.2%
t 27
 
9.9%
o 25
 
9.1%
n 23
 
8.4%
i 22
 
8.0%
r 20
 
7.3%
s 17
 
6.2%
p 15
 
5.5%
g 13
 
4.7%
h 12
 
4.4%
Other values (12) 72
26.3%
Decimal Number
ValueCountFrequency (%)
2 5
38.5%
1 4
30.8%
0 2
 
15.4%
4 1
 
7.7%
8 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
. 41
56.2%
/ 26
35.6%
: 6
 
8.2%
Space Separator
ValueCountFrequency (%)
1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 274
75.7%
Common 88
 
24.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 28
 
10.2%
t 27
 
9.9%
o 25
 
9.1%
n 23
 
8.4%
i 22
 
8.0%
r 20
 
7.3%
s 17
 
6.2%
p 15
 
5.5%
g 13
 
4.7%
h 12
 
4.4%
Other values (12) 72
26.3%
Common
ValueCountFrequency (%)
. 41
46.6%
/ 26
29.5%
: 6
 
6.8%
2 5
 
5.7%
1 4
 
4.5%
0 2
 
2.3%
4 1
 
1.1%
1
 
1.1%
8 1
 
1.1%
_ 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 362
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 41
 
11.3%
w 28
 
7.7%
t 27
 
7.5%
/ 26
 
7.2%
o 25
 
6.9%
n 23
 
6.4%
i 22
 
6.1%
r 20
 
5.5%
s 17
 
4.7%
p 15
 
4.1%
Other values (22) 118
32.6%

건설사업비(백만원)
Real number (ℝ)

MISSING 

Distinct35
Distinct (%)100.0%
Missing8
Missing (%)18.6%
Infinite0
Infinite (%)0.0%
Mean38940.429
Minimum120
Maximum321800
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-22T21:34:50.185214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum120
5-th percentile1546
Q13204.5
median8366
Q349240.5
95-th percentile133904
Maximum321800
Range321680
Interquartile range (IQR)46036

Descriptive statistics

Standard deviation65960.131
Coefficient of variation (CV)1.6938727
Kurtosis9.4018525
Mean38940.429
Median Absolute Deviation (MAD)6366
Skewness2.785731
Sum1362915
Variance4.3507388 × 109
MonotonicityNot monotonic
2023-12-22T21:34:51.035862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
5000 1
 
2.3%
4890 1
 
2.3%
8881 1
 
2.3%
1420 1
 
2.3%
4865 1
 
2.3%
321800 1
 
2.3%
77400 1
 
2.3%
2000 1
 
2.3%
25436 1
 
2.3%
72748 1
 
2.3%
Other values (25) 25
58.1%
(Missing) 8
 
18.6%
ValueCountFrequency (%)
120 1
2.3%
1420 1
2.3%
1600 1
2.3%
2000 1
2.3%
2084 1
2.3%
2501 1
2.3%
2554 1
2.3%
2798 1
2.3%
2928 1
2.3%
3481 1
2.3%
ValueCountFrequency (%)
321800 1
2.3%
169359 1
2.3%
118709 1
2.3%
114397 1
2.3%
108800 1
2.3%
105967 1
2.3%
77400 1
2.3%
72748 1
2.3%
57181 1
2.3%
41300 1
2.3%

비고사항
Text

MISSING 

Distinct21
Distinct (%)100.0%
Missing22
Missing (%)51.2%
Memory size476.0 B
2023-12-22T21:34:51.987501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length22
Mean length20.52381
Min length6

Characters and Unicode

Total characters431
Distinct characters90
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st row부지 및 사업비는 고양종합운동장 포함
2nd row육상경기장 내 축구장 포함
3rd row테니스장 4, 배드민턴장 3, 게이트볼장 1
4th row게이트볼장, 풋살장, 테니스장 1면, 농구장, 부대시설 포함(체육센터 부지 제외)
5th row부대시설, 다목적구장, 족구장 1면 포함(테니스장, 롤러스케이트장, 구기체육관은 별도 현황으로 기재)
ValueCountFrequency (%)
1면 6
 
6.4%
테니스장 6
 
6.4%
포함 4
 
4.3%
2 4
 
4.3%
족구장 4
 
4.3%
게이트볼장 4
 
4.3%
1 4
 
4.3%
주경기장 3
 
3.2%
보조경기장 3
 
3.2%
부지 2
 
2.1%
Other values (46) 54
57.4%
2023-12-22T21:34:53.394090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
77
17.9%
장 47
 
10.9%
, 27
 
6.3%
면 17
 
3.9%
구 17
 
3.9%
1 15
 
3.5%
기 12
 
2.8%
스 11
 
2.6%
경 10
 
2.3%
니 9
 
2.1%
Other values (80) 189
43.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 286
66.4%
Space Separator 77
 
17.9%
Decimal Number 35
 
8.1%
Other Punctuation 28
 
6.5%
Close Punctuation 2
 
0.5%
Open Punctuation 2
 
0.5%
Other Symbol 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 47
 
16.4%
면 17
 
5.9%
구 17
 
5.9%
기 12
 
4.2%
스 11
 
3.8%
경 10
 
3.5%
니 9
 
3.1%
테 9
 
3.1%
트 8
 
2.8%
이 7
 
2.4%
Other values (68) 139
48.6%
Decimal Number
ValueCountFrequency (%)
1 15
42.9%
2 7
20.0%
5 4
 
11.4%
3 4
 
11.4%
4 4
 
11.4%
6 1
 
2.9%
Other Punctuation
ValueCountFrequency (%)
, 27
96.4%
. 1
 
3.6%
Space Separator
ValueCountFrequency (%)
77
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 286
66.4%
Common 145
33.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 47
 
16.4%
면 17
 
5.9%
구 17
 
5.9%
기 12
 
4.2%
스 11
 
3.8%
경 10
 
3.5%
니 9
 
3.1%
테 9
 
3.1%
트 8
 
2.8%
이 7
 
2.4%
Other values (68) 139
48.6%
Common
ValueCountFrequency (%)
77
53.1%
, 27
 
18.6%
1 15
 
10.3%
2 7
 
4.8%
5 4
 
2.8%
3 4
 
2.8%
4 4
 
2.8%
) 2
 
1.4%
( 2
 
1.4%
㎡ 1
 
0.7%
Other values (2) 2
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 286
66.4%
ASCII 144
33.4%
CJK Compat 1
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
77
53.5%
, 27
 
18.8%
1 15
 
10.4%
2 7
 
4.9%
5 4
 
2.8%
3 4
 
2.8%
4 4
 
2.8%
) 2
 
1.4%
( 2
 
1.4%
6 1
 
0.7%
Hangul
ValueCountFrequency (%)
장 47
 
16.4%
면 17
 
5.9%
구 17
 
5.9%
기 12
 
4.2%
스 11
 
3.8%
경 10
 
3.5%
니 9
 
3.1%
테 9
 
3.1%
트 8
 
2.8%
이 7
 
2.4%
Other values (68) 139
48.6%
CJK Compat
ValueCountFrequency (%)
㎡ 1
100.0%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct29
Distinct (%)87.9%
Missing10
Missing (%)23.3%
Infinite0
Infinite (%)0.0%
Mean14212.182
Minimum10110
Maximum18591
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-22T21:34:53.826221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10110
5-th percentile10223
Q111320
median13830
Q317321
95-th percentile18588
Maximum18591
Range8481
Interquartile range (IQR)6001

Descriptive statistics

Standard deviation3002.9588
Coefficient of variation (CV)0.21129471
Kurtosis-1.4812571
Mean14212.182
Median Absolute Deviation (MAD)2818
Skewness0.16932239
Sum469002
Variance9017761.8
MonotonicityNot monotonic
2023-12-22T21:34:54.399521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
10223 3
 
7.0%
18588 2
 
4.7%
11012 2
 
4.7%
18436 1
 
2.3%
18591 1
 
2.3%
11154 1
 
2.3%
17799 1
 
2.3%
17903 1
 
2.3%
10933 1
 
2.3%
17321 1
 
2.3%
Other values (19) 19
44.2%
(Missing) 10
23.3%
ValueCountFrequency (%)
10110 1
 
2.3%
10223 3
7.0%
10933 1
 
2.3%
11012 2
4.7%
11154 1
 
2.3%
11320 1
 
2.3%
11606 1
 
2.3%
12244 1
 
2.3%
12416 1
 
2.3%
12625 1
 
2.3%
ValueCountFrequency (%)
18591 1
2.3%
18588 2
4.7%
18436 1
2.3%
18131 1
2.3%
17903 1
2.3%
17799 1
2.3%
17508 1
2.3%
17321 1
2.3%
17152 1
2.3%
16308 1
2.3%

소재지지번주소
Text

MISSING 

Distinct30
Distinct (%)88.2%
Missing9
Missing (%)20.9%
Memory size476.0 B
2023-12-22T21:34:55.165404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length22.5
Mean length19.764706
Min length14

Characters and Unicode

Total characters672
Distinct characters101
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)79.4%

Sample

1st row경기도 가평군 가평읍 대곡리 316번지
2nd row경기도 고양시 일산서구 대화동 2320번지
3rd row경기도 고양시 일산서구 대화동 2320번지
4th row경기도 고양시 일산서구 대화동 2320번지
5th row경기도 과천시 관문동 3번지
ValueCountFrequency (%)
경기도 34
 
21.8%
화성시 4
 
2.6%
일산서구 3
 
1.9%
대화동 3
 
1.9%
2320번지 3
 
1.9%
향남읍 3
 
1.9%
고양시 3
 
1.9%
옥산리 2
 
1.3%
평택시 2
 
1.3%
성남시 2
 
1.3%
Other values (91) 97
62.2%
2023-12-22T21:34:56.832926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
122
18.2%
도 36
 
5.4%
경 35
 
5.2%
기 34
 
5.1%
지 34
 
5.1%
번 32
 
4.8%
시 31
 
4.6%
동 26
 
3.9%
2 17
 
2.5%
3 15
 
2.2%
Other values (91) 290
43.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 440
65.5%
Space Separator 122
 
18.2%
Decimal Number 104
 
15.5%
Dash Punctuation 6
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 36
 
8.2%
경 35
 
8.0%
기 34
 
7.7%
지 34
 
7.7%
번 32
 
7.3%
시 31
 
7.0%
동 26
 
5.9%
구 11
 
2.5%
리 10
 
2.3%
산 10
 
2.3%
Other values (79) 181
41.1%
Decimal Number
ValueCountFrequency (%)
2 17
16.3%
3 15
14.4%
1 15
14.4%
0 13
12.5%
6 12
11.5%
8 8
7.7%
7 8
7.7%
5 6
 
5.8%
4 5
 
4.8%
9 5
 
4.8%
Space Separator
ValueCountFrequency (%)
122
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 440
65.5%
Common 232
34.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 36
 
8.2%
경 35
 
8.0%
기 34
 
7.7%
지 34
 
7.7%
번 32
 
7.3%
시 31
 
7.0%
동 26
 
5.9%
구 11
 
2.5%
리 10
 
2.3%
산 10
 
2.3%
Other values (79) 181
41.1%
Common
ValueCountFrequency (%)
122
52.6%
2 17
 
7.3%
3 15
 
6.5%
1 15
 
6.5%
0 13
 
5.6%
6 12
 
5.2%
8 8
 
3.4%
7 8
 
3.4%
- 6
 
2.6%
5 6
 
2.6%
Other values (2) 10
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 440
65.5%
ASCII 232
34.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
122
52.6%
2 17
 
7.3%
3 15
 
6.5%
1 15
 
6.5%
0 13
 
5.6%
6 12
 
5.2%
8 8
 
3.4%
7 8
 
3.4%
- 6
 
2.6%
5 6
 
2.6%
Other values (2) 10
 
4.3%
Hangul
ValueCountFrequency (%)
도 36
 
8.2%
경 35
 
8.0%
기 34
 
7.7%
지 34
 
7.7%
번 32
 
7.3%
시 31
 
7.0%
동 26
 
5.9%
구 11
 
2.5%
리 10
 
2.3%
산 10
 
2.3%
Other values (79) 181
41.1%

소재지도로명주소
Text

MISSING 

Distinct24
Distinct (%)85.7%
Missing15
Missing (%)34.9%
Memory size476.0 B
2023-12-22T21:34:57.586892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length22
Mean length18.321429
Min length15

Characters and Unicode

Total characters513
Distinct characters90
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)75.0%

Sample

1st row경기도 가평군 가평읍 문화로 131
2nd row경기도 고양시 일산서구 중앙로 1601
3rd row경기도 고양시 일산서구 중앙로 1601
4th row경기도 고양시 일산서구 중앙로 1601
5th row경기도 과천시 중앙로 294
ValueCountFrequency (%)
경기도 28
 
21.5%
중앙로 5
 
3.8%
일산서구 3
 
2.3%
1601 3
 
2.3%
고양시 3
 
2.3%
문화로 3
 
2.3%
화성시 3
 
2.3%
향남읍 3
 
2.3%
향남로 2
 
1.5%
평택시 2
 
1.5%
Other values (70) 75
57.7%
2023-12-22T21:34:59.306735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
102
19.9%
경 31
 
6.0%
기 29
 
5.7%
로 28
 
5.5%
도 28
 
5.5%
시 25
 
4.9%
1 24
 
4.7%
6 14
 
2.7%
0 12
 
2.3%
천 10
 
1.9%
Other values (80) 210
40.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 323
63.0%
Space Separator 102
 
19.9%
Decimal Number 87
 
17.0%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 31
 
9.6%
기 29
 
9.0%
로 28
 
8.7%
도 28
 
8.7%
시 25
 
7.7%
천 10
 
3.1%
남 9
 
2.8%
읍 8
 
2.5%
구 8
 
2.5%
중 7
 
2.2%
Other values (68) 140
43.3%
Decimal Number
ValueCountFrequency (%)
1 24
27.6%
6 14
16.1%
0 12
13.8%
2 8
 
9.2%
5 7
 
8.0%
9 6
 
6.9%
8 5
 
5.7%
7 4
 
4.6%
4 4
 
4.6%
3 3
 
3.4%
Space Separator
ValueCountFrequency (%)
102
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 323
63.0%
Common 190
37.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 31
 
9.6%
기 29
 
9.0%
로 28
 
8.7%
도 28
 
8.7%
시 25
 
7.7%
천 10
 
3.1%
남 9
 
2.8%
읍 8
 
2.5%
구 8
 
2.5%
중 7
 
2.2%
Other values (68) 140
43.3%
Common
ValueCountFrequency (%)
102
53.7%
1 24
 
12.6%
6 14
 
7.4%
0 12
 
6.3%
2 8
 
4.2%
5 7
 
3.7%
9 6
 
3.2%
8 5
 
2.6%
7 4
 
2.1%
4 4
 
2.1%
Other values (2) 4
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 323
63.0%
ASCII 190
37.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
102
53.7%
1 24
 
12.6%
6 14
 
7.4%
0 12
 
6.3%
2 8
 
4.2%
5 7
 
3.7%
9 6
 
3.2%
8 5
 
2.6%
7 4
 
2.1%
4 4
 
2.1%
Other values (2) 4
 
2.1%
Hangul
ValueCountFrequency (%)
경 31
 
9.6%
기 29
 
9.0%
로 28
 
8.7%
도 28
 
8.7%
시 25
 
7.7%
천 10
 
3.1%
남 9
 
2.8%
읍 8
 
2.5%
구 8
 
2.5%
중 7
 
2.2%
Other values (68) 140
43.3%

WGS84위도
Real number (ℝ)

MISSING 

Distinct30
Distinct (%)88.2%
Missing9
Missing (%)20.9%
Infinite0
Infinite (%)0.0%
Mean37.457841
Minimum36.98852
Maximum38.107025
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-22T21:34:59.978744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.98852
5-th percentile37.024204
Q137.250155
median37.412539
Q337.675685
95-th percentile37.9726
Maximum38.107025
Range1.1185049
Interquartile range (IQR)0.4255293

Descriptive statistics

Standard deviation0.30055793
Coefficient of variation (CV)0.008023899
Kurtosis-0.43819115
Mean37.457841
Median Absolute Deviation (MAD)0.23197118
Skewness0.48785186
Sum1273.5666
Variance0.090335071
MonotonicityNot monotonic
2023-12-22T21:35:00.989303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
37.6756846 3
 
7.0%
37.13786295 2
 
4.7%
38.10702468 2
 
4.7%
37.29335558 1
 
2.3%
37.20393926 1
 
2.3%
37.13336199 1
 
2.3%
37.88847519 1
 
2.3%
37.03065854 1
 
2.3%
36.98851982 1
 
2.3%
37.75609246 1
 
2.3%
Other values (20) 20
46.5%
(Missing) 9
20.9%
ValueCountFrequency (%)
36.98851982 1
2.3%
37.012216 1
2.3%
37.03065854 1
2.3%
37.13336199 1
2.3%
37.13786295 2
4.7%
37.15719652 1
2.3%
37.20393926 1
2.3%
37.23780012 1
2.3%
37.28722085 1
2.3%
37.29335558 1
2.3%
ValueCountFrequency (%)
38.10702468 2
4.7%
37.90021716 1
 
2.3%
37.88847519 1
 
2.3%
37.8248742 1
 
2.3%
37.75756895 1
 
2.3%
37.75609246 1
 
2.3%
37.6756846 3
7.0%
37.61743924 1
 
2.3%
37.60683867 1
 
2.3%
37.503069 1
 
2.3%

WGS84경도
Real number (ℝ)

MISSING 

Distinct30
Distinct (%)88.2%
Missing9
Missing (%)20.9%
Infinite0
Infinite (%)0.0%
Mean127.04345
Minimum126.72002
Maximum127.62416
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-22T21:35:01.862563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.72002
5-th percentile126.74254
Q1126.92241
median127.04632
Q3127.13362
95-th percentile127.49968
Maximum127.62416
Range0.9041373
Interquartile range (IQR)0.2112072

Descriptive statistics

Standard deviation0.22334727
Coefficient of variation (CV)0.0017580385
Kurtosis0.51229795
Mean127.04345
Median Absolute Deviation (MAD)0.1239129
Skewness0.74879966
Sum4319.4773
Variance0.049884004
MonotonicityNot monotonic
2023-12-22T21:35:02.801432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
126.7425418 3
 
7.0%
126.9224111 2
 
4.7%
127.0805049 2
 
4.7%
127.6241613 1
 
2.3%
127.0635525 1
 
2.3%
126.9289882 1
 
2.3%
127.2005478 1
 
2.3%
126.9432937 1
 
2.3%
127.1082554 1
 
2.3%
126.7857331 1
 
2.3%
Other values (20) 20
46.5%
(Missing) 9
20.9%
ValueCountFrequency (%)
126.720024 1
 
2.3%
126.7425418 3
7.0%
126.7857331 1
 
2.3%
126.7988743 1
 
2.3%
126.8153228 1
 
2.3%
126.856295 1
 
2.3%
126.9224111 2
4.7%
126.9289882 1
 
2.3%
126.9364021 1
 
2.3%
126.9432937 1
 
2.3%
ValueCountFrequency (%)
127.6241613 1
2.3%
127.507218 1
2.3%
127.4956237 1
2.3%
127.3279763 1
2.3%
127.2516416 1
2.3%
127.2132386 1
2.3%
127.2005478 1
2.3%
127.176618 1
2.3%
127.1379572 1
2.3%
127.1206016 1
2.3%

Sample

집계년도시군명시설명소유기관명운영조직명관리주체명준공연도부지면적(㎡)건축면적(㎡)연면적(㎡)트랙바닥재료명트랙주로연장(m)트랙주로수필드바닥재료명필드폭(m)필드길이(m)관람석좌석수수용인원수(명)좌석형태명연락처홈페이지주소건설사업비(백만원)비고사항소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
02021가평군가평종합운동장가평군문화체육시설담당시설관리공단199362903.01314.01599.0우레탄4008인조잔디6810531655000계단식+토성잔디031-580-2765www.ga21.net4726<NA>12416경기도 가평군 가평읍 대곡리 316번지경기도 가평군 가평읍 문화로 13137.824874127.507218
12021고양시고양종합운동장 보조경기장고양시<NA>고양도시관리공사2003305350.0675.25463.0천연탄성고무4008천연잔디6810510001000의자식<NA><NA><NA>부지 및 사업비는 고양종합운동장 포함10223경기도 고양시 일산서구 대화동 2320번지경기도 고양시 일산서구 중앙로 160137.675685126.742542
22021고양시덕양 별무리경기장고양시<NA>고양도시관리공사2004164242.01077.01360.0천연탄성고무4008인조잔디6410124252425의자식<NA><NA>5000<NA>10223경기도 고양시 일산서구 대화동 2320번지경기도 고양시 일산서구 중앙로 160137.675685126.742542
32021고양시고양종합운동장고양시고양시시설관리공단고양도시관리공사2003305350.025569.059689.0천연탄성고무4008천연잔디681054300043000의자식031-929-4800<NA>114397<NA>10223경기도 고양시 일산서구 대화동 2320번지경기도 고양시 일산서구 중앙로 160137.675685126.742542
42021과천시관문체육공원 운동장과천시과천시시설관리공단시설관리공단2001179635.0578.63931.3우레탄4008인조잔디6810550006100목재계단식<NA>citizenshall.or.kr16162육상경기장 내 축구장 포함13830경기도 과천시 관문동 3번지경기도 과천시 중앙로 29437.440914126.996746
52021광명시노온정수장 다목적운동장광명시<NA>광명도시공사201034010.0<NA><NA>몬도4008인조잔디6810510001000<NA><NA><NA>5815<NA>14302경기도 광명시 노온사동 2-1번지<NA>37.449103126.856295
62021광주시광주시 공설운동장광주시광주시광주시200631667.0<NA><NA>몬도4005인조잔디641041000010000계단식<NA><NA>1600테니스장 4, 배드민턴장 3, 게이트볼장 112755경기도 광주시 경안동 123-4번지경기도 광주시 파발로 17637.414749127.251642
72021군포시복합생활스포츠타운 운동장군포시<NA>시설관리공단201478777.0<NA><NA>복합탄성고무34314인조잔디5890562562<NA><NA><NA><NA>게이트볼장, 풋살장, 테니스장 1면, 농구장, 부대시설 포함(체육센터 부지 제외)<NA><NA><NA><NA><NA>
82021군포시시민체육광장 운동장군포시군포시 청소년과 체육시설팀시설관리공단200368898.0<NA><NA>우레탄4008인조잔디7010512481300의자식031-390-0418http://www.gunpo21.net/2084부대시설, 다목적구장, 족구장 1면 포함(테니스장, 롤러스케이트장, 구기체육관은 별도 현황으로 기재)15862경기도 군포시 금정동 871번지<NA>37.354281126.936402
92021김포시김포시 종합운동장김포시김포시시설관리공단위탁 (김포도시공사)199332573.03502.03818.0쳔연탄성고무4008인조잔디68105506810000계단식<NA>gimposisul.or.kr/4595테니스장 3면10110경기도 김포시 사우동 290번지경기도 김포시 돌문로15번길 2037.617439126.720024
집계년도시군명시설명소유기관명운영조직명관리주체명준공연도부지면적(㎡)건축면적(㎡)연면적(㎡)트랙바닥재료명트랙주로연장(m)트랙주로수필드바닥재료명필드폭(m)필드길이(m)관람석좌석수수용인원수(명)좌석형태명연락처홈페이지주소건설사업비(백만원)비고사항소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
332021파주시파주스타디움 (공설운동장)파주시<NA>파주시2004158101.016701.023423.0몬도4008천연잔디681052300025000<NA><NA><NA>72748테니스장5면 궁도장 1면 등10933경기도 파주시 금릉동 186-5번지경기도 파주시 중앙로 16037.756092126.785733
342021파주시파주스타디움 (보조경기장)파주시<NA>파주시200635607.0<NA><NA>몬도1406인조잔디68105696696<NA><NA><NA>2798<NA><NA><NA><NA><NA><NA>
352021평택시소사벌레포츠타운 종합운동장평택시평택시체육시설 운영사업소평택시198718037.03465.03465.0우레탄4008천연잔디681051273815000의자식031-659-4921www.pyongta.go.kr2928<NA>17903경기도 평택시 합정동 392번지경기도 평택시 평남로 61636.98852127.108255
362021평택시평택 서부 공설운동장평택시평택시체육시설 운영사업소평택시199612248.02614.01852.0토사4008천연잔디681051000012000의자식031-659-4921www.pyongta.go.kr4664<NA>17799경기도 평택시 청북읍 후사리 265-1번지경기도 평택시 청북읍 서해로 1528-1837.030659126.943294
372021포천시포천종합운동장포천시주민자치과시설관리공단199053401.04832.08248.0우레탄4008천연잔디6810559647000의자식031-530-8079<NA>3481씨름장 1면11154경기도 포천시 군내면 구읍리 691번지경기도 포천시 군내면 호국로 151837.888475127.200548
382021하남시하남종합운동장 주경기장하남시시설관리공단하남도시공사200728587.02219.04303.0천연탄성고무4008인조잔디681051205712057<NA><NA>osan.go.kr57181<NA><NA><NA><NA><NA><NA>
392021화성시화성종합경기타운 주경기장화성시<NA>화성도시공사2011285097.054020.5965076.55몬도트랙4008천연잔디681053527035270<NA><NA><NA>169359<NA>18588경기도 화성시 향남읍 도이리 668번지경기도 화성시 향남읍 향남로 47037.137863126.922411
402021화성시도원체육공원 인조잔디구장화성시<NA>화성도시공사200914350.0<NA><NA>몬도트랙4008인조잔디68105<NA><NA><NA><NA><NA><NA><NA>18591경기도 화성시 향남읍 행정리 478번지경기도 화성시 향남읍 행정동로 9637.133362126.928988
412021화성시동탄센트럴파크 인조잔디구장화성시<NA>화성도시공사20088400.0<NA><NA><NA>3006인조잔디5590<NA><NA><NA><NA><NA><NA><NA>18436경기도 화성시 반송동 59<NA>37.203939127.063553
422021화성시화성종합경기타운 보조경기장화성시<NA>화성도시공사2011<NA>1499.921712.57몬도트랙4008천연잔디6810520022002<NA><NA><NA><NA>부지면적, 사업비는 화성종합 경기타운 주경기장 포함18588경기도 화성시 향남읍 도이리 668번지경기도 화성시 향남읍 향남로 47037.137863126.922411